Decoding the Temporal Structures and Interactions of Multiple Face Dimensions Using Optically Pumped Magnetometer Magnetoencephalography (OPM-MEG).

Humans possess a remarkable ability to rapidly access diverse information from others' faces with just a brief glance, which is crucial for intricate social interactions. While previous studies using event-related potentials/fields have explored various face dimensions during this process, the interplay between these dimensions remains unclear. Here, by applying multivariate decoding analysis to neural signals recorded with optically pumped magnetometer magnetoencephalography, we systematically investigated the temporal interactions between invariant and variable aspects of face stimuli, including race, gender, age, and expression. First, our analysis revealed unique temporal structures for each face dimension with high test-retest reliability. Notably, expression and race exhibited a dominant and stably maintained temporal structure according to temporal generalization analysis. Further exploration into the mutual interactions among face dimensions uncovered age effects on gender and race, as well as expression effects on race, during the early stage (∼200-300 ms postface presentation). Additionally, we observed a relatively late effect of race on gender representation, peaking ∼350 ms after the stimulus onset. Taken together, our findings provide novel insights into the neural dynamics underlying the multidimensional aspects of face perception and illuminate the promising future of utilizing OPM-MEG for exploring higher-level human cognition.